Database Security Challenges
Security Challenges of the Greatest Database
When working with data, more is nearly always better. Larger source material can provide a more comprehensive model of the subject matter. A greater understanding can be gleaned, and that leads to better algorithms of meeting current and future needs. Trends can be predicted and prepared for, as well as understanding the most likely outcome of situations. Each new addition of data can contribute to a more expansive understanding of a subject, and this ideology has led to the creation of Big Data. This information is analyzed and used in ways that have revolutionized aspects of the social and business worlds in ways we can only speculate at. However, it creates new issues. Where does that level of information come from, and how is it stored? More importantly, how is Big Data kept safe from those that would misuse it? The concept of big data is not new. Most know the reference of 1984 and Big Brother. That concept was begun back in 1949. That Orwellian book remains a part of our consciousness even now, though Big Data, the possible realization of the concept, is far younger.
Functioning Big Data
To create a security structure for Big Data, several aspects need to be addressed. Security, executives, and administrators must find a way to manage sources, frameworks, and analytics. The source of big data is of course varied. From simple traffic data of who is visiting what sites online to personally identifying information, card payment data, intellectual property, medical records, social media, video files, spreadsheets, and dozens more all can contribute to a digital footprint for each person. With the population of America alone over 324 million people, the amount of data is nothing short of staggering.
And yet, each individual is a wealth of information on trends for purchasing, voting, personal views, education, and a host of other aspects. Each individual then contributes to an ever-expanding whole and becomes part of a community, town, area, county, state, and country. Such is not the end of the expansion, but it is a steady expansion of trends all contributed to by each person online. Big Data must learn to collate that data from the myriad of sources, and make it available in a way that is compatible. Applications and databases of unstructured data continues to flow in, and without processing, it is useless. Made a cohesive database however, it becomes invaluable.
Which leads to the framework. Big Data, regardless of the environment it is stored on, handles staggering amounts of information. The sensitive nature of much of it must be managed appropriately. That data can reside on a server, a data node, or come in the form of configuration files, error logs, system logs, or any of an innumerable amount of file types. However, this leads to the analytics. The information may be invaluable, but only in the untold number of uses it has. The ability to process the storehouses of Big Data is the real prize. The emerging trends and possibilities gleaned from the collected information of millions of people can lead to incredible innovation. This is only possible if it can be properly analyzed and put to appropriate use.
Each company has secrets and proprietary information. The security measures vary from company to company, but the idea that sensitive information must be kept safe is somewhat universal. Applied to Big Data, you have all business and personal data being processed. The ultimate database of our time, and is worthy of a similar level of security attention. Security cannot be relegated to simply protecting specific nodes or endpoints. Any information has three sections: the origin point, often a database, transmission, and the endpoint. Each requires a level of security, and monitoring Big Data for security is a daunting task.
Currently, the system is so large that multiple security approaches are each being applied to individual areas. Imagine a police force across the country, but individual laws vary wildly. No homogeneous security currently can contend with the scope of big data, leaving security measures to clash with fragmented key and policy management. This presents more than a security headache, it presents performance issues as each area must be sated individually and slows analytics. Several companies are vying to provide a comprehensive security option for Big Data, but none have yet emerged to create a single source. An argument can be made to prevent such from happening.
Each year, consumers are encouraged to either update or replace virus protection software. The reasoning is malicious individuals are constantly developing new and innovative ways to bypass security. With the most tantalizing database in history available, the same will be true of any protection for Big Data. Despite performance hindrances, each different form of protection for Big Data actually reinforces the security of the whole. One source would create 1984 as a single authority can have all data. If that singular authority is bypassed in some way, a malicious entity would have the ability to see everything. Changing information at will, or determining secret information that could be disastrous. The subject of securing Big Data and all the analytics it promises is vitally important- but perhaps a group effort is far more effective than any singular source. If one is compromised, at least Big Data is not.